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Field
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develops and applies methods for uncertainty quantification, engineering reliability, and risk & decision analysis to support optimal and sustainable decision-making in engineering and environmental systems
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and exchanges. In addition to a strong core in cutting-edge Mathematical Analysis, the program offers distinctive opportunities for interdisciplinary collaboration in economics, finance, decision theory
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, technologies and systems. The ERAM group within TSL have great experience in SSbD, especially in combining different methods such as modeling mass flows analysis (MFA), Life cycle analysis (LCA) and semi
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the relationship between tyre operating conditions and friction behaviour, new characterisation and analysis techniques are required. In partnership with Mercedes-Benz Grand Prix Ltd, this PhD research will combine
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incentives, behavioural drivers, and land-use decisions at the meso-scale (e.g. river basins or regions), using clear case studies. You develop modelling approaches that bridge economic analysis and spatial
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 10 days ago
with setting up a streamflow forecasting system in Portugal and the advancement of scientific knowledge in machine learning probabilistic hydrological forecasting and decision-making optimized to act on
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of the PRIDAS is developing and providing data science support services, processing and analysis methods, as well as management of highly complex multimodal data. Our research with primates involves a combination
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different methods such as modeling mass flows analysis (MFA), Life cycle analysis (LCA) and semi-quantitative methods for decision support for sustainable innovation. PhD Student in Safe and Sustainable Green
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presenting research results orally. Good understanding of life cycle assessment (LCA), its methodology, and analysis using software (e.g., OpenLCA, SimaPro). Experience of laboratory and field sampling and
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science, connected to MDU’s existing research areas. The PhD project focuses on the development of a large language model (LLM)-based AI agent specialized in energy decision-making, including: development of AI models